Orientation‐Selective Memory Switching in Quasi‐1D NbSe<sub>3</sub> Neuromorphic Device for Omnibearing Motion Detection
Intelligent neuromorphic hardware holds considerable promise in addressing the growing demand for massive real-time data processing in edge computing. Resistive switching materials with intrinsic anisotropy and a compact design of non-volatile memory devices with the capability of handling spatiotemporally reconstructed data is crucial to perform sophisticated tasks in complex application scenarios. In this study, an anisotropic resistive switching cell with a planar configuration based on lithiated NbSe<sub>3</sub> nanosheets is demonstrated. Benefitting from the highly aligned diffusive channel associated with a quasi-1D van der Waals structure, the memristor patterned along NbSe<sub>3</sub> atomic chains presents robust memory switching behavior with superior stability, particularly the low set/reset voltages (0.4 V/-0.36 V) and extremely small standard deviation (0.041 V/0.051 V), among the best compared to state-of-the-art devices. More importantly, unlike traditional resistive switching materials, anisotropic ion migration in NbSe<sub>3</sub> crystals leads to a high orientation selectivity in the conductance update. Custom-designed neuromorphic hardware contributes to the implementation of omnibearing motion recognition for automatic pilot applications, yielding a high accuracy of 95.9% considering variations. This article presents a new strategy based on NbSe<sub>3</sub> crystals to develop a neuromorphic computing system with intelligent application scenarios.
Authors
- Cheng‐Yan Xu (ORCID: https://orcid.org/0000-0002-7835-6635)
- Feichi Zhou (ORCID: https://orcid.org/0000-0001-7756-1082)
- Peiyu Huang (ORCID: https://orcid.org/0000-0003-4226-9369)
- Ruo‐Yao Sun
- Jing‐Kai Qin (ORCID: https://orcid.org/0000-0002-0737-3614)
- Chengyi Zhu (ORCID: https://orcid.org/0000-0002-2919-5177)
- Zhen Hu (ORCID: https://orcid.org/0000-0002-0160-782X)
- Bingxuan Zhu
- Qing Chen (ORCID: https://orcid.org/0000-0002-7919-5159)
- Zeyu Hou
- Liang Zhen
Institutions
- Shenzhen Institute of Information Technology (CN)
- Harbin Institute of Technology (CN)
- Southern University of Science and Technology (CN)
Publication Details
- Journal
- Advanced Materials
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1002/adma.202409017
- Citations
- 14
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.92
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province
- National Key Research and Development Program of China